A Possible Pitfall in the Experimental Analysis of Tampering Detection Algorithms

2014 ◽  
Author(s):  
Giuseppe Cattaneo ◽  
Gianluca Roscigno
Keyword(s):  
Experimental Analysis ◽  
Tampering Detection ◽  
Detection Algorithms

scholarly journals Image Forensic Tool (IFT)

2021 ◽  
Vol 13 (6) ◽  
pp. 1-15
Author(s):  
Digambar Pawar ◽  
Mayank Gajpal
Keyword(s):  
State Of The Art ◽  
Digital Signatures ◽  
Tamper Detection ◽  
Digital Evidence ◽  
Prototype Model ◽  
Cyber Crime ◽  
Tampering Detection ◽  
Detection Algorithms ◽  
Image Forensic ◽  
Art Works

Images now-a-days are often used as an authenticated proof for any cyber-crime. Images that do not remain genuine can mislead the court of law. The fast and dynamically growing technology doubts the trust in the integrity of images. Tampering mostly refers to adding or removing important features from an image without leaving any obvious trace. In earlier days, digital signatures were used to preserve the integrity, but now a days various tools are available to tamper digital signatures as well. Even in various state-of-the-art works in tamper detection, there are various restrictions in the type of inputs and the type of tampering detection. In this paper, the researchers propose a prototype model in the form of a tool that will retrieve all the image files from given digital evidence and detect tampering in the images. For various types of tampering, different tampering detection algorithms have been used. The proposed prototype will detect if tampering has been done or not and will classify the image files into groups based on the type of tampering.

An Experimental Analysis of Community Detection Algorithms on a Temporally Evolving Dataset

2021 ◽  
pp. 23-70
Author(s):  
B.S.A.S. Rajita ◽  
Mrinalini Shukla ◽  
Deepa Kumari ◽  
Subhrakanta Panda
Keyword(s):  
Community Detection ◽  
Experimental Analysis ◽  
Detection Algorithms

Detection of Montage in Lossy Compressed Digital Audio Recordings

2015 ◽  
Vol 39 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Rafał Korycki
Keyword(s):  
Audio Coding ◽  
Digital Audio ◽  
Tampering Detection ◽  
Detection Algorithms ◽  
Perceptual Audio Coding ◽  
Audio Recordings ◽  
Spectral Coefficients ◽  
Previous Algorithm ◽  
Audio Files ◽  
Music Database

Abstract This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. Presented approach is based on frame offset measurement in audio files compressed and decoded by using perceptual audio coding algorithms which employ modified discrete cosine transform. The minimum values of total number of active MDCT coefficients occur for frame shifts equal to multiplications of applied window length. Any modification of audio file, including cutting off or pasting a part of audio recording causes a disturbance within this regularity. In this study the algorithm based on checking frame offset previously described in the literature is expanded by using each of four types of analysis windows commonly applied in the majority of MDCT based encoders. To enhance the robustness of the method additional histogram analysis is performed by detecting the presence of small value spectral components. Moreover, computation of maximum values of nonzero spectral coefficients is employed, which creates a gating function for the results obtained based on previous algorithm. This solution radically minimizes a number of false detections of forgeries. The influence of compression algorithms' parameters on detection of forgeries is presented by applying AAC and Ogg Vorbis encoders as examples. The effectiveness of tampering detection algorithms proposed in this paper is tested on a predefined music database and compared graphically using ROC-like curves.

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